Emotion Recognition in Conversation

67 papers with code • 12 benchmarks • 13 datasets

Given the transcript of a conversation along with speaker information of each constituent utterance, the ERC task aims to identify the emotion of each utterance from several pre-defined emotions. Formally, given the input sequence of N number of utterances [(u1, p1), (u2, p2), . . . , (uN , pN )], where each utterance ui = [ui,1, ui,2, . . . , ui,T ] consists of T words ui,j and spoken by party pi, the task is to predict the emotion label ei of each utterance ui. .

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Use these libraries to find Emotion Recognition in Conversation models and implementations

Curriculum Learning Meets Directed Acyclic Graph for Multimodal Emotion Recognition

vanntc711/multidag-cl 27 Feb 2024

Emotion recognition in conversation (ERC) is a crucial task in natural language processing and affective computing.

2
27 Feb 2024

Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

alibaba-damo-academy/FunASR 14 Nov 2023

Recently, instruction-following audio-language models have received broad attention for audio interaction with humans.

2,866
14 Nov 2023

From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed Dialogues

lcs2-iiitd/emnlp-coffee 19 Oct 2023

Recognizing that emotional intelligence encompasses a comprehension of worldly knowledge, we propose an innovative approach that integrates commonsense information with dialogue context to facilitate a deeper understanding of emotions.

1
19 Oct 2023

InstructERC: Reforming Emotion Recognition in Conversation with a Retrieval Multi-task LLMs Framework

LIN-SHANG/InstructERC 21 Sep 2023

The field of emotion recognition of conversation (ERC) has been focusing on separating sentence feature encoding and context modeling, lacking exploration in generative paradigms based on unified designs.

92
21 Sep 2023

UniSA: Unified Generative Framework for Sentiment Analysis

dawn0815/UniSA 4 Sep 2023

Sentiment analysis is a crucial task that aims to understand people's emotional states and predict emotional categories based on multimodal information.

35
04 Sep 2023

RBA-GCN: Relational Bilevel Aggregation Graph Convolutional Network for Emotion Recognition

luftmenscher/RBA-GCN 18 Aug 2023

This module can construct the interaction between different modalities and capture long-range contextual information based on similarity clusters.

1
18 Aug 2023

FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion Recognition

ludybupt/FATRER 23 Jul 2023

This paper concentrates on the understanding of interlocutors' emotions evoked in conversational utterances.

11
23 Jul 2023

A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party Conversations

NUSTM/FacialMMT Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2023

With the extracted face sequences, we propose a multimodal facial expression-aware emotion recognition model, which leverages the frame-level facial emotion distributions to help improve utterance-level emotion recognition based on multi-task learning.

38
01 Jul 2023

Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and Paraphrasing

nlpwm-whu/mplp 11 Jun 2023

It is a challenging task since the recognition of the emotion in one utterance involves many complex factors, such as the conversational context, the speaker's background, and the subtle difference between emotion labels.

6
11 Jun 2023

Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations

zerohd4869/sacl 2 Jun 2023

To address this, we propose a supervised adversarial contrastive learning (SACL) framework for learning class-spread structured representations in a supervised manner.

25
02 Jun 2023